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Journal Article

OBD Diagnostic Strategies for LEVIII Exhaust Gas Aftertreatment Concepts

2015-04-14
2015-01-1040
Upcoming motor vehicle emission regulations, such as California's LEVIII, continue to tighten emission limitations in diesel vehicles. These increasingly challenging emission requirements will be met by improving the combustion process (reducing engine-out emissions), as well as improving the exhaust gas aftertreatment efficiency. Furthermore, intricate On-Board Diagnostics (OBD) systems are required to properly diagnose and meet OBD regulation requirements for complex aftertreatment systems. Under these conditions, current monitoring strategies are unable to guarantee reliable detection of partially failed systems. Additionally, new OBD regulations require aftertreatment systems to be diagnosed as a whole. This paper covers potential OBD strategies for LEVIII aftertreatment concepts with regard to regulation compliance and robustness, while striving to use existing sensor concepts.
Technical Paper

Beyond Digital Twin, Innovative Use of AI/ML Technology from Ideation to Design of Next Generation Electric Drive Systems

2024-04-09
2024-01-2862
Accelerated adoption of electric propulsion system in mobility industry has stressed the time and iterations of product development cycle which was traditionally known to go over multiple iterations and phases. Current market demands a timely introduction of compelling products that brings high value to end user. Further, a growing emphasis over reducing mineral content using sustainable options and process, adds further complexity to multi-objective-optimization of electric drive systems. At BorgWarner our engineers use Digital-Twins, physics-based models which closely represent BorgWarner products in greater dept (physics) thus allowing an improved assessment of product design (components and systems) to target application at very early stage in product development. The spring success with Digital-Twin, BorgWarner furthered enhanced the model through introducing Artificial Intelligent (AI) and Machine Learning (ML) technologies in both modelling and virtual sensing.
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